The need for technological solutions to learning is abundant. In particular, there exists an unfulfilled need for an intelligent and interactive interface system that is able to respond to user inquiries as well as partake in role playing simulations.
Role play simulation involves a simulation in which a user of a computer system interacts with an alternate system. The alternate system accepts and responds to the user with natural language in a manner consistent with how an actual human might behave. Hence, role play simulation provides users with a method enhancing interpersonal skills by engaging in conversations in a real context.
The need for role play simulation as an educational tool follows from showings that role playing is an effective technique for teaching interactive skills as well as a substitute for skills gained through experience. Role playing in classrooms is often ineffective, however, because of the inability to realistically capture the essence of a simulation and the inability to give precise feedback.
Tangential attempts have been made to satisfy such a demand through the formulation of computerized information systems which respond to inquiries made in natural language. The primary application for natural language interfaces has been to natural language database query systems. For all natural language systems, the user has been required to type his question into the keyboard of a computer terminal. When the entire question had been input, the natural language interface attempts to process an input query, or otherwise respond that the query was not understood.
Natural language information retrieval systems are provided with a semantic analysis unit for processing natural language. The semantic analysis unit is designed so as to understand the semantics of an inquiry sentence inputted in a natural language, produce retrieval conditions, and ultimately carry out an information retrieval.
In order for the semantic analysis unit of the system to understand the semantics of words contained within an inquiry sentence, it is required to collate a word with a dictionary and carry out a semantic analysis. It is, however, impossible to register all words, which might be contained in a great variety of inquiry sentences, within a dictionary. Therefore, it follows that a portion of the words within the inquiry sentence, such as an undefined word, are not capable of being collated.
Tennant (1980) performed the first and only extensive evaluation of a natural language interface. S This evaluation was performed for the PLANES system, a natural language database query system that accessed a military aircraft maintenance database in natural language. The results of this evaluation show quite clearly why natural language interfaces are not in common use today. About one-third of the queries input to the system by users were incomprehensible by the system, even though the problems assigned these users were specifically designed to correspond with relatively straightforward queries.
Although research into the construction of natural language interfaces has gone on for a number of years, resulting in the construction of many prototype systems, natural language interfaces are not in common use today. One reason for this is that the natural language interfaces that have been constructed to date are overly complex to construct and quite difficult to utilize. Another reason is because all systems that are constructed have many limitations in coverage. That is, the constructed systems can only understand a small subset of all possible natural language queries. A natural language system which can understand all, or even a substantial part of a language, is currently not feasible.
A further reason why natural language interfaces are not in common use today is the large amount of time it has traditionally taken to construct a natural language interface. Current technology is such that each natural language interface must be constructed on a case by case basis for each application. Efforts taking from ten to thirty man years per application are not uncommon. Thus, only applications that can justify such a large expenditure of manpower are candidates for possible applications. However, given the quality of the system that results, the effort has not proven to be worthwhile.
Natural language interfaces that have been constructed employ a grammar which characterizes the class of acceptable input strings. A parser then accesses this grammar to produce a parse tree (or parse trees for an ambiguous input) for the input string. This parse tree is then translated into an expression (or set of expressions) which represents the meaning of an input string and which is interpretable by the computer system for which the natural language interface has been built. A wide variety of intricate grammar formalisms and parsing algorithms have been utilized in such interfaces.
Most grammar formalisms can, however, be classified under the general heading of augmented context-free grammars. Augmented context-free grammars are basic grammar rules of a context-free grammar where each context-free rule has, associated with it, augmentations which give the grammar added power. These augmentations generally access attributes (and sometimes values) of the nodes of the context-free rules.
Linguistic theories based on this class of grammars are those of Gazdar (1982), Bresnan and Kaplan (see Kaplan and Bresnan, 1981 and Bresnan, 1982), and Ross and Saenz (see Ross, 1981 and Saenz, 1982). Parsers for constructing natural language interfaces which utilize grammars of this general class are the DIAMOND Parser developed at SRI (see J. Robinson, 1980), the GPSG Parser developed at HP (see Gawron, King, Lamping, Loebner, Paulson, Pullum, Sag, and Wasow, 1982) and many others. Note that this description is neutral between syntactically-based and semantically-based grammars. In general, these frameworks are adequate for characterizing both classes of grammars.
Natural language parsers are generally based on one of several parsing algorithms that have been employed for parsing context-free grammars (for example, see Earley, 1980, Younger, 1967, Griffiths and Petrick, 1965, and Ross, 1981). First, a context-free parse is performed. Then, the augmentation rules are used. In some systems, a partial context-free parse is initially undertaken. Thereafter, augmentations which are relevant to that portion of the parse are undertaken. This procedure is then iterated until a complete parse is found.
A notable exception to this general trend is the TAQ System that has been under development for the past ten years at IBM (see Plath, 1975 and Petrick, 1973). It is based on the theory of transformational grammar (see Chomsky, 1965) and it employs, as grammar rules, several hundred inverse transformations. A transformational parser applies relevant transformations to yield a set of parse trees.
Because of the numerous problems associated with natural language systems, a number of alternative "restricted natural language systems" have been developed. Restricted natural language systems allow a user to select inquiry sentences. The selected inquiry sentence is then always capable of being interpretable and processed by the underlying system.
U.S. Pat. No. 4,829,423, issued to Tennant et. al., is an example of a restricted natural language system. The Tennant patent discloses a system employing diverse menus from which an inquiry is formulated from beginning to end. At any point in the construction of an inquiry, only a subset of the menus is active. That is, only those menus containing words which are determined to be likely continuations of immediately previously selected words are displayed for selection.
Valid continuations are determined by a parser which uses a predefined grammar to determine which words are valid continuations from a previously selected word, and whether a complete inquiry sentence has been entered. The disclosed system does not, however, preclude the formation of ambiguous inquiries.
Current restricted natural language systems, such as the menu-based system disclosed in the Tennant patent, require a user to undertake a complex and ineffective process in order to formulate an inquiry. Specifically, current restricted natural language systems construct an inquiry sentence from left to right. Unfortunately, the initial words of a sentence may be highly variable, unrelated to the final content of the sentence, or dependent upon the latter words of the inquiry. Moreover, such systems do not protect against ambiguous inquiries. Thus, the prior art that the applicant is aware of provides an interface that is overly complex and ineffective for formulating typical inquiry sentences.